基于机器视觉的立铣刀磨损检测方法的研究

Research on End Mill Wear Detection Based on Machine VisionAbstractIn the milling process,there is inevitably end mill wear.when the wear and tear is nottimely feedback to the staff,it will be impossible to meet the accuracy requirements for a largenumber of parts,and may lead to a large number of parts being incomplete within the specifiedtime,which make work efficiency reduce and the progress of work be affected.In this paper,the wear of the end milling cutter is detected by computer during the end milling cutter change.According to the test results,we can judge whether the replacement end milling cutter cancontinue to be used in time.Through the analysis of the various forms of wear and the various testing methods of thewear of the end mill,the testing method suitable for the processing conditions in this article isselected,and according to the blunt standard of the tool given in the internationalstandard,milling the judge of the eligibility.In this paper,it is necessary to calibrate the camera because it is necessary to study thewear image of the milling cutter.In the process of calibration,the camera parameters calculatedfrom multiple images are summarized and optimized by genetic algorithm.Finally,the optimaldistortion parameters of the camera are obtained,and the image correction is realized.In the pre-processing of wear images,Considering vibration noise and other environmentof the machine tool,it is necessary to preprocess the collected images to prevent the influenceon the calculation of the later eigenvalues.The gray level and denoising process are selected.Inthe process of noise processing,the method of adaptive median filtering is selected,which cannot only remove the noise well,but also protect the image information well.After thede-noising image is still some information is lost,and the latter by enhanced image processing,which makes the image denois and the original image information be well protected.When extracting the eigenvalues of each wear quantity of the image,it is necessary todetect the edge of the image after preprocessing,to compare the first and second order edgedetection operators and to select the optimal Canny operator.Canny operator is used to extractthe wear image of the end milling cutter,the edge of the end milling cutter without noise isobtained.However,this method is only suitable for edge detection of whole pixels,but not forsubpixel edge detection with high accuracy.In this paper,the former operator of Zernike moment is improved,the template isamplified.And through the experimental verification of each operator,the rationality of the